SLIDE 96 Ascent Energy, Inc Holt #1-19 TICORA Geosciences, Inc.
8 and sulfur free basis are presented in Equations 1, 2, 3, and 4 respectively. Appendix B includes the raw gas storage capacity data. Gsma = Gs• 1/(1 – wae) (1) Gsa = Gs• 1/(1 – wme – wae) (2) Gsi = Gsa• (1 – wmi – wai) (3) Gsa&s = Gs• 1/(1 – wme – wae – wse) (4) Where:
Gs gas storage capacity, scf/ton Gsma moist, ash free gas storage capacity, scf/ton Gsa dry, ash free gas storage capacity, scf/ton Gsi in-situ gas storage capacity, sfc/ton Gsa&s dry, ash and sulfur free gas storage capacity, scf/ton wme experimentally determined moisture weight fraction wae experimentally determined ash weight fraction wse experimentally determined total sulfur fraction wmi in-situ moisture weight fraction wai in-situ ash weight fraction
To construct a mathematical fit to the resulting data, the Langmuir model is used. Plotting equilibrium pressure divided by calculated storage capacity vs. equilibrium pressure produces a linear relationship. The intercept and slope of the resulting linear function are used to produce the “Langmuir Parameters” (Langmuir pressure and Langmuir volume). Once the Langmuir parameters are determined one can model the gas storage capacity at any pressure. The mathematical model is defined by Equation 5. Appendix C includes the raw Langmuir regression data. Gs = GsL•p / (p+PL) (5) Where:
Gs gas storage capacity, scf/ton p pressure, psia GsL Langmuir Volume, sfc/ton PL Langmuir Pressure, psia
3.5 Sample Unloading Once the sorption isotherm test has been completed, the sample cell pressure is reduced to slightly above atmospheric
- pressure. The sample begins to desorb the gas sorbed during the sorption isotherm test, causing the pressure inside the
sample cell to rise. The pressure build up reduces repeatedly until all gas has been desorbed. The sample is then unloaded and a small aliquot is removed for post-isotherm MHC determination. Post-isotherm MHC is conducted in triplicate and the moisture content is compared to the MHC determined prior to isotherm analysis. This is done to ensure that the moisture content has remained stable and to ensure that the storage capacity results do indeed reflect in-situ conditions.
4.0 GAS STORAGE CAPACITY UNCERTAINTY AND ERROR PROPAGATION 1
There are systematic and random errors associated with isotherm measurements. The systematic errors result from improper sample preparation and handling, use of an experimental temperature different from the actual reservoir temperature, errors in gas z factor estimates, and poor equipment calibration practices. Condensation of the sorbing gas
- f interest within the sample or reference cells can also occur when testing relatively high critical temperature gases
(CO2, C2H6, C3H8 for example), even at temperatures below the critical temperature. Examples of random errors are those that result from unintended exceptions to standard sample preparation procedures, cell pressure and temperature variations caused by laboratory condition and oil bath temperature variations, and temperature and pressure measurement fluctuations caused by electronic equipment and electrical power variations. In an effort to reduce these errors, TICORA uses the most accurate gas density correlations available. All pressure transducers, thermocouples, and mass balances are calibrated or checked before each measurement. TICORA requests that the clients take special care in estimating reservoir temperature before requesting sorption isotherm analysis. The condensation conditions for gases are accurately known and avoided. We have reduced random errors by construction
- f an isolated, insulated, and temperature controlled isotherm laboratory that includes high quality (and expensive)